OpenMetadata/openmetadata-docs/content/openmetadata/connectors/messaging/kafka/cli.md

---
title: Run Kafka Connector using the CLI
slug: /openmetadata/connectors/messaging/kafka/cli
---

# Run Kafka using the metadata CLI

In this section, we provide guides and references to use the Kafka connector.

Configure and schedule Kafka metadata and profiler workflows from the OpenMetadata UI:
- [Requirements](#requirements)
- [Metadata Ingestion](#metadata-ingestion)

## Requirements

<InlineCallout color="violet-70" icon="description" bold="OpenMetadata 0.12 or later" href="/deployment">
To deploy OpenMetadata, check the <a href="/deployment">Deployment</a> guides.
</InlineCallout>

To run the Ingestion via the UI you'll need to use the OpenMetadata Ingestion Container, which comes shipped with
custom Airflow plugins to handle the workflow deployment.

### Python Requirements

To run the Kafka ingestion, you will need to install:

```bash
pip3 install "openmetadata-ingestion[kafka]"
```

## Metadata Ingestion

All connectors are defined as JSON Schemas.
[Here](https://github.com/open-metadata/OpenMetadata/blob/main/catalog-rest-service/src/main/resources/json/schema/entity/services/connections/messaging/kafkaConnection.json)
you can find the structure to create a connection to Kafka.

In order to create and run a Metadata Ingestion workflow, we will follow
the steps to create a YAML configuration able to connect to the source,
process the Entities if needed, and reach the OpenMetadata server.

The workflow is modeled around the following
[JSON Schema](https://github.com/open-metadata/OpenMetadata/blob/main/catalog-rest-service/src/main/resources/json/schema/metadataIngestion/workflow.json)

### 1. Define the YAML Config

This is a sample config for Kafka:

```yaml
source:
  type: kafka
  serviceName: local_kafka
  serviceConnection:
    config:
      type: Kafka
      bootstrapServers: localhost:9092
      schemaRegistryURL: http://localhost:8081  # Needs to be a URI
      consumerConfig: {}
      schemaRegistryConfig: {}
  sourceConfig:
    config:
      topicFilterPattern:
        excludes:
          - _confluent.*
        # includes:
        #   - topic1
      generateSampleData: true
sink:
  type: metadata-rest
  config: {}
workflowConfig:
  # loggerLevel: DEBUG  # DEBUG, INFO, WARN or ERROR
  openMetadataServerConfig:
    hostPort: http://localhost:8585/api
    authProvider: no-auth

```

#### Source Configuration - Service Connection

- **bootstrapServers**: Kafka bootstrap servers. Add them in comma separated values ex: host1:9092,host2:9092.
- **schemaRegistryURL**: Confluent Kafka Schema Registry URL. URI format.
- **consumerConfig**: Confluent Kafka Consumer Config.
- **schemaRegistryConfig**:Confluent Kafka Schema Registry Config.

#### Source Configuration - Source Config

The sourceConfig is defined [here](https://github.com/open-metadata/OpenMetadata/blob/main/catalog-rest-service/src/main/resources/json/schema/metadataIngestion/messagingServiceMetadataPipeline.json):

- `generateSampleData`: Option to turn on/off generating sample data during metadata extraction.
- `topicFilterPattern`: Note that the `topicFilterPattern` supports regex as include or exclude. E.g.,

```yaml
topicFilterPattern:
  includes:
    - users
    - type_test
```

#### Sink Configuration

To send the metadata to OpenMetadata, it needs to be specified as `type: metadata-rest`.

#### Workflow Configuration

The main property here is the `openMetadataServerConfig`, where you can define the host and security provider of your OpenMetadata installation.

For a simple, local installation using our docker containers, this looks like:

```yaml
workflowConfig:
  openMetadataServerConfig:
    hostPort: http://localhost:8585/api
    authProvider: no-auth
```

We support different security providers. You can find their definitions [here](https://github.com/open-metadata/OpenMetadata/tree/main/catalog-rest-service/src/main/resources/json/schema/security/client).
You can find the different implementation of the ingestion below.

<Collapse title="Configure SSO in the Ingestion Workflows">

### Auth0 SSO

```yaml
workflowConfig:
  openMetadataServerConfig:
    hostPort: 'http://localhost:8585/api'
    authProvider: auth0
    securityConfig:
      clientId: '{your_client_id}'
      secretKey: '{your_client_secret}'
      domain: '{your_domain}'
```

### Azure SSO

```yaml
workflowConfig:
  openMetadataServerConfig:
    hostPort: 'http://localhost:8585/api'
    authProvider: azure
    securityConfig:
      clientSecret: '{your_client_secret}'
      authority: '{your_authority_url}'
      clientId: '{your_client_id}'
      scopes:
        - your_scopes
```

### Custom OIDC SSO

```yaml
workflowConfig:
  openMetadataServerConfig:
    hostPort: 'http://localhost:8585/api'
    authProvider: custom-oidc
    securityConfig:
      clientId: '{your_client_id}'
      secretKey: '{your_client_secret}'
      domain: '{your_domain}'
```

### Google SSO

```yaml
workflowConfig:
  openMetadataServerConfig:
    hostPort: 'http://localhost:8585/api'
    authProvider: google
    securityConfig:
      secretKey: '{path-to-json-creds}'
```

### Okta SSO

```yaml
workflowConfig:
  openMetadataServerConfig:
    hostPort: http://localhost:8585/api
    authProvider: okta
    securityConfig:
      clientId: "{CLIENT_ID - SPA APP}"
      orgURL: "{ISSUER_URL}/v1/token"
      privateKey: "{public/private keypair}"
      email: "{email}"
      scopes:
        - token
```

### Amazon Cognito SSO

The ingestion can be configured by [Enabling JWT Tokens](https://docs.open-metadata.org/deployment/security/enable-jwt-tokens)

```yaml
workflowConfig:
  openMetadataServerConfig:
    hostPort: 'http://localhost:8585/api'
    authProvider: auth0
    securityConfig:
      clientId: '{your_client_id}'
      secretKey: '{your_client_secret}'
      domain: '{your_domain}'
```

### OneLogin SSO

Which uses Custom OIDC for the ingestion

```yaml
workflowConfig:
  openMetadataServerConfig:
    hostPort: 'http://localhost:8585/api'
    authProvider: custom-oidc
    securityConfig:
      clientId: '{your_client_id}'
      secretKey: '{your_client_secret}'
      domain: '{your_domain}'
```

### KeyCloak SSO

Which uses Custom OIDC for the ingestion

```yaml
workflowConfig:
  openMetadataServerConfig:
    hostPort: 'http://localhost:8585/api'
    authProvider: custom-oidc
    securityConfig:
      clientId: '{your_client_id}'
      secretKey: '{your_client_secret}'
      domain: '{your_domain}'
```

</Collapse>

### 2. Run with the CLI

First, we will need to save the YAML file. Afterward, and with all requirements installed, we can run:

```bash
metadata ingest -c <path-to-yaml>
```

Note that from connector to connector, this recipe will always be the same. By updating the YAML configuration,
you will be able to extract metadata from different sources.